Comments (3)
I'd have to check. I think it's used as both as an indexing limit and as a
constant, and it was simpler to get good behavior assuming it was an int,
so fancy indexing would be sure to work.
If we go to N_tot x K instead of K x K x N, then a lot of the fancy
indexing requirement disappears, though.
On Thu, Sep 12, 2013 at 7:55 PM, kyleabeauchamp [email protected]:
Does it make sense to use float everywhere for N_k as a way to avoid silly
integer arithmetic issues / casting issues? I suppose there is a slight
reduction in resolution when doing this, but I don't think it's
relevant--the resolution of a float64 is 1E-15...—
Reply to this email directly or view it on GitHubhttps://github.com//issues/23
.
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Can we just recast N_k internally as a numpy.array float32 or float64, thereby allowing the user to pass in whatever (list, array, integers, floats) and have it all work fine internally once it is stored as a class field?
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I don't we need to worry about this, seems working fine.
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